An interference elimination method for synaesthesia integrated system based on segmented channel estimation

Abstract

The present invention discloses a method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation. The method comprises the following steps: establishing a channel model and a data transmission model for a non-cellular collaborative synaesthesia integrated system; transmitting an uplink pilot signal through all users, and having a central processing unit (CPU) estimate the data transmission channel between the user and the access node (AP); transmitting a target detection signal through all downlink access nodes (APs); jointly receiving the signal through all uplink access nodes (APs); and detecting whether the perceived target is in the scene; transmitting a downlink pilot signal through all downlink access nodes (APs); and obtaining an estimate of the cross-link interference channel between the access nodes (APs); and simultaneously performing uplink and downlink communications and sensing the target's moving direction and speed. Based on the channel estimation results, the method performs interference elimination processing on the received communication and sensing signals. The present invention can effectively and directly suppress system interference and improve communication and sensing performance.

Description

Technical Field

[0001] The present invention belongs to the technical field of cooperative synaesthesia integration of non-cellular large-scale MIMO systems, and in particular relates to a synaesthesia integration system interference elimination method based on segmented channel estimation. Background Art

[0002] ISAC technology can significantly improve system spectrum efficiency and reduce implementation costs while integrating communication and perception functions by sharing spectrum resources and reusing hardware architecture. It is very suitable for emerging technologies such as the Internet of Vehicles and drones. The collaborative ISAC system based on non-cellular massive MIMO is a powerful supporting architecture for realizing the 6G intelligent connection of all things. In the non-cellular massive MIMO system, multiple access nodes AP are connected to a central processing unit CPU, which operates all access nodes to serve all user devices through coherent transmission and reception, and completes the perception of targets in the scene through the collaborative transmission and reception of perception signals by downlink access nodes and uplink access nodes.

[0003] However, cooperative telepathy systems based on non-cellular massive MIMO suffer from numerous highly coupled and difficult-to-handle interferences, including cross-link interference between uplink users and downlink users, cross-link interference between downlink access nodes and uplink access nodes, and interference between communication and perception signals. Existing interference mitigation schemes in cooperative telepathy technologies indirectly mitigate the effects of these interferences through resource scheduling optimization algorithms such as power allocation, precoding design, and receiver design. No direct interference mitigation schemes have been proposed. Therefore, it is necessary to design effective telepathy interference mitigation schemes through direct interference elimination. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation, so as to solve the problem that there is no direct interference elimination solution in the prior art, and to effectively and directly suppress system interference and improve communication and perception performance.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation comprises the following steps:

[0007] Step 1: Establish a channel model and data transmission model for the non-cellular cooperative interawareness integrated system. All users send uplink pilot signals, and the central processing unit (CPU) estimates the data transmission channel between the user and the access node (AP), where the access node (AP) includes an uplink access node (AP) and a downlink access node (AP).

[0008] Step 2: All downlink access nodes (APs) send a target detection signal, all uplink access nodes (APs) jointly receive the signal and transmit it to the central processing unit (CPU). The CPU detects whether the target is in the scene.

[0009] Step 3: All downlink access nodes (APs) send downlink pilot signals. The central processing unit (CPU) uses the pilot signals received from all uplink access nodes (APs) and the target detection result obtained in step 2 to estimate the cross-link interference channel between the access nodes (APs).

[0010] In step 4, the non-cellular cooperative interawareness integrated system simultaneously performs uplink and downlink communications and perceives the target's moving direction and speed, and performs interference elimination processing on the received communication and perception signals based on the channel estimation results obtained in steps 1 and 3.

[0011] The step 1 specifically includes:

[0012] Step 101: In a non-cellular cooperative interawareness integrated system, a regional scene model managed by a central processing unit (CPU) is established; wherein M access nodes (APs) and K users are distributed; and M of the M access nodes (APs) are connected to the network. ul work in uplink mode, and the remaining M dl Work in downlink mode; K users include K ul Uplink demand users and K dl Downlink users; each access point (AP) is equipped with N antennas and connected to the central processing unit (CPU) via a fronthaul link. At the same time, there is a target with an uncertain location in the scenario. The non-cellular cooperative interawareness integrated system needs to simultaneously complete uplink communication with users with uplink needs, downlink communication with users with downlink needs, and perceive the target's moving direction and speed.

[0013] Using the fast fading channel model, the channel conditions in each coherent time block remain unchanged, and the channel in the non-cellular cooperative synaesthesia integrated system scenario is modeled: let k be any integer in the set [1, K], m be any integer in the set [1, M], and the channel vector from the kth user to the mth access node AP is recorded as a vector with N rows and 1 column in, represents the large-scale fading coefficient between the k-th user and the m-th access node AP, express The small-scale fast fading vector, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of I N represents the identity matrix with N rows and columns;

[0014] In the same way, let j be the set [1,K ul ], l is any integer in the set [1,K dl ], the channel from the jth uplink user to the lth downlink user is recorded as a complex number Let u be the set [1,M ul ], i is any integer in the set [1,M dl ] is any integer in the range of , the direct channel without target reflection between the uth uplink access node AP and the ith downlink access node AP is recorded as an N-row N-column complex matrix in, represents the large-scale fading coefficient, express The small-scale fast fading matrix, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of ;

[0015] The existence of the target will cause a channel reflected by the target to exist between the uplink access node AP and the downlink access node AP. The target reflection channel between the uth uplink access node AP and the ith downlink access node AP is recorded as an N-row N-column complex matrix Among them, θ RCS and Represent the path loss coefficient and radar cross section coefficient respectively; a ul,u and a dl,i is a vector with N rows and 1 column, representing the steering vector from the uth uplink access node AP and the ith downlink access node AP to the target, with the superscript symbol (·) H Indicates the conjugate transpose operation on the matrix; since the existence of the target is unknown to the central processing unit CPU, the target existence symbol δ is established T To indicate whether the target appears in the scene, δ T =0 means it does not exist, δ T =1 means existence; since the position of the target is unknown, the CPU obtains the prior target reflection channel through prior knowledge and records it as

[0016] Step 102, the first τ in each coherent time block p symbols are used to estimate the data transmission channel between the user and the access node AP, τ p Indicates the number of symbols occupied in the first stage; in this stage, K users randomly select pilot signals to send, and the uplink pilot signal received by the mth access node AP is represented by an N-line τ p Column matrix For channel estimation from the kth user to the mth access node AP, we need to first Multiply by the pilot signal sent by the kth user get

[0017]

[0018] Among them, ρ p represents the user's pilot transmission power, represents the set of sequence numbers of users using the same pilot as the k-th user and does not include k, represents the channel from the k'th user to the mth access node AP, is the additive Gaussian white noise matrix from the kth user to the mth access node AP, which has a mean of 0 and a variance of The complex Gaussian distribution of

[0019] According to the minimum mean square error (MMSE) channel estimation method, the channel estimation for the kth user to the mth access node AP in this coherent time block is obtained.

[0020]

[0021] in, Indicates taking the mean of the values in the brackets. yes The equivalent large-scale fading coefficient of represents the large-scale fading coefficient of the channel between the kth user and the mth access node AP, represents the large-scale fading coefficient of the channel between the k'th user and the mth access node AP, represents the set of serial numbers of users using the same pilot as the k-th user, express The small-scale fast fading vector, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of The channel estimation error is recorded as represents the channel estimation error vector from the kth user to the mth access node AP.

[0022] The step 2 specifically includes:

[0023] Step 201, in each coherent time block (τ p +1)~(τ p +τ s ) symbols are used to detect whether the perceived target is in the scene, τ s Table 2: The number of symbols occupied by the second stage; in this stage, all downlink access nodes AP send target detection signals, and all uplink access nodes AP jointly receive the signals and detect the presence of the perceived target;

[0024] Let t be the set [1,τ s ] is any integer in the tth time slot of this phase, the N rows and 1 column target detection signal received by the uth uplink access node AP Expressed as

[0025]

[0026] in, is the N-row, 1-column detection signal sent by the i-th downlink access node AP in the t-th time slot of the second phase, is the additive white noise received by the nth uplink access node AP in the tth time slot of the second phase, which obeys symbol means that it has zero mean and a correlation coefficient of The multivariate cyclically symmetric complex Gaussian distribution of is the variance of the channel noise;

[0027] Step 202: ul The signals received by the uplink access nodes AP in the tth time slot are vertically linked to obtain M ul A vector with N rows and 1 column Represents the signal received by the central processing unit CPU in the tth time slot, where and Represent the 1st and Mth ul The uplink access node AP receives the target detection signal in the tth time slot, and the superscript symbol (·) T Indicates the transposition operation of the matrix; direct channels between all access nodes AP After vectorization, vertical connection follows the distribution symbol Represents a matrix with zero mean and variance R AA The multivariate cyclically symmetric complex Gaussian distribution of It is a direct channel between all access nodes AP The variance matrix of the distribution after vectorization, diag{·} represents the diagonal matrix established with the vector in the brackets as the diagonal, represents the large-scale fading coefficient of the direct channel between the ath uplink access node AP and the bth downlink access node AP, Indicates that both rows and columns are N 2 The identity matrix; the target reflection channel between all access nodes AP After vectorization, vertical connection follows the distribution symbol Indicates that the mean is and the variance matrix R ATAThe multivariate cyclically symmetric complex Gaussian distribution of It is the target reflection a priori channel between access nodes APs known to all central processing units (CPUs) The vector connected vertically after vectorization, R ATA is the variance matrix of the distribution obeyed by the target reflection channel between all access nodes AP after vectorization;

[0028] The maximum a posteriori ratio test (MAPRT) is used to use this stage τ s The signal received by the CPU in each time slot is used to detect whether the target exists. The maximum a posteriori ratio test target detection formula Λ is expressed as

[0029]

[0030] in

[0031]

[0032] exp(·) represents the exponential function operation, det(·) represents the determinant operation of the matrix, and ||·|| represents the Euclidean norm operation of the vector; It is the aggregate signal of the sensing signals sent by all downlink access nodes AP in the tth time slot. and Represents the 1st and Mth dl The detection signal sent by the downlink access node AP in the tth time slot of the second phase is: represents the Kronecker product, Indicates that both rows and columns are M ul The identity matrix of

[0033] Set the comparison threshold Λ det,Th , when the central processing unit CPU calculates Λ≥Λ det,Th When the CPU thinks that the target exists in the scene, the target has an estimated symbol When the central processing unit CPU calculates Λ<Λ det,Th When the CPU thinks that the target does not exist in the scene, the target has an estimated symbol

[0034] The step 3 specifically includes:

[0035] Step 301, in each coherent time block (τ p +τ s +1)~(τ p +τ s +τ dp ) symbols are used to estimate the cross-link interference channel between access nodes AP τdp The number of symbols occupied by the third stage; and when δ T =0 When δ T =1

[0036] In this phase, all antennas of all downlink access nodes AP send mutually orthogonal downlink pilots; let n be any integer in the set [1, N], and the pilot sent by the nth antenna of the i-th downlink access node AP is denoted as The downlink pilot signal received by the uth uplink access node AP Expressed as

[0037]

[0038] Among them, ρ dp is the transmit power of the downlink pilot, represents the channel vector from the nth antenna of the i-th downlink access node AP to the u-th access node AP, is the additive Gaussian white noise matrix of the uth uplink access node AP at this stage, which has a mean of 0 and a variance of The complex Gaussian distribution of

[0039] Step 302: Obtain the channel estimation vector from the nth antenna of the i-th downlink access node AP to the u-th access node AP in this coherent time block according to the minimum mean square error (MMSE) channel estimation method. Expressed as

[0040]

[0041] in, Indicates taking the mean of the values in the brackets, Cov(·,·) indicates taking the covariance matrix operation of the vector in the brackets, At the same time, because the CPU cannot know the target exists symbol δ T , the target existence estimation symbol can only be obtained through the second stage Therefore, it is necessary to δ in T Replace with get That is, the channel estimation from the nth antenna of the i-th downlink access node AP to the n-th access node AP obtained by the central processing unit CPU in the third stage.

[0042] The step 4 specifically includes:

[0043] Step 401: The non-cellular cooperative synaesthesia integrated system simultaneously performs uplink and downlink communications and perceives the target's moving direction and speed. At this time, each downlink access node AP sends a synaesthesia integrated signal containing a downlink communication signal and a perception signal. The signal sent by the i-th downlink access node is in, represents the communication precoding vector of the i-th downlink access node to the l-th downlink user, Represents the communication signal to the lth downlink user; represents the perceptual precoding vector of the i-th downlink access node, represents the perception signal of the i-th downlink access node;

[0044] The received signal of the lth downlink user is expressed as:

[0045]

[0046] in, represents the communication signal that the lth downlink user expects to obtain, represents the channel estimation from the lth downlink user to the i-th downlink access node AP; Indicates the communication interference of other downlink users, represents the communication precoding vector of the i-th downlink access node to the l'th downlink user, Represents the communication signal for the l'th downlink user; represents the interference caused by the channel estimation error between the user and the access node AP, represents the channel estimation error from the lth downlink user to the i-th downlink access node AP, represents the communication precoding vector of the i-th downlink access node to the k-th downlink user, represents the communication signal for the kth downlink user; Indicates the interference caused by the perceived signal, represents the channel estimation error from the lth downlink user to the i-th downlink access node AP; represents the cross-link interference, ρ ul,j represents the transmit power of the jth uplink user, represents the communication signal of the jth uplink user; represents the noise interference of the lth downlink user;

[0047] According to the desired signal and interference signal received by the lth downlink user, a high-precision downlink communication signal can be demodulated;

[0048] Step 402: The received signal of the uth uplink access node AP is expressed as

[0049]

[0050] in, Indicates the transmission signal of all uplink users, Indicates the communication signal of all downlink access nodes AP, Represents the noise received by the u-th uplink access node AP at this stage; the estimated channel between access nodes AP obtained in the third stage is eliminated Cross-link interference in

[0051]

[0052] in is the cross-link interference estimation channel matrix from the u-th uplink access node AP to the i-th downlink access node AP, and They represent the channel estimation from the 1st antenna of the i-th downlink access node AP to the u-th access node AP and the channel estimation from the Nth antenna of the i-th downlink access node AP to the u-th access node AP respectively; ρ ul,j represents the transmit power of the jth uplink user, represents the communication signal of the jth uplink user; is the cross-link interference channel matrix from the u-th uplink access node AP to the i-th downlink access node AP;

[0053] The signal of the jth uplink user received by the central processing unit CPU is expressed as:

[0054]

[0055] Among them, v uj represents the maximum ratio combining receiver vector of the jth uplink user’s signal received by the uth uplink access node AP, represents the communication signal that the lth downlink user expects to obtain, represents the channel estimate from the jth uplink user to the uth uplink access node AP; represents the communication interference of other downlink users, ρ ul,j' represents the transmit power of the j'th uplink user, represents the channel estimation from the j'th uplink user to the uth uplink access node AP, represents the communication signal of the j'th uplink user;

[0056] represents the interference caused by the channel estimation error between the user and the access node AP, ρ ul,k represents the transmit power of the kth uplink user, represents the channel estimation error from the kth uplink user to the uth uplink access node AP, represents the communication signal of the kth uplink user; Indicates the interference caused by the perceived signal, is the cross-link interference estimation channel error matrix from the u-th uplink access node AP to the i-th downlink access node AP; Indicates cross-link interference; Indicates noise interference;

[0057] The CPU can demodulate the high-precision uplink communication signal based on the desired signal and interference signal of the jth uplink user received by the CPU.

[0058] Step 403: The signal received by the uth uplink access node AP When performing sensory signal detection, it is reformulated as:

[0059]

[0060] in, represents the perception signal that the u-th uplink access node AP expects to obtain; Indicates uplink communication signal interference, represents the channel vector from the kth uplink user to the uth uplink access node AP; Indicates downlink communication signal interference;

[0061] Based on the decoding of the uplink and downlink communication signals in steps 401 and 402, After communication interference elimination, it is expressed as in, Indicates the residual uplink communication signal interference after interference elimination. is the decoding error of the u-th uplink user signal; Indicates the residual downlink communication signal interference after interference elimination;

[0062] A high-precision perception signal can be demodulated based on the perception expectation signal and the perception interference signal received by the central processing unit CPU.

[0063] Beneficial Effects: The present invention's interference cancellation method for a telepathic integrated system based on segmented channel estimation has the following advantages: It addresses the complex interference challenges inherent in a cellular-free collaborative telepathic integrated system, fully leveraging the advantages of the high concentration and coverage of a cellular-free architecture. Direct interference cancellation significantly improves the system's communication and perception performance. The present invention first establishes a model of channels, transmission signals, and interference based on the system scenario. Next, it derives the estimated channel and estimated error channel for data transmission between users and access nodes (APs) after sending an uplink pilot. A target detection inequality is then established to detect the presence of a perceived target in the scenario, and the estimated channel and estimated error channel for cross-link interference between APs after sending a downlink pilot are derived. Finally, an interference cancellation method and sequential processing order based on the estimated channel are proposed for simultaneous full-duplex communication and target perception. Compared to existing indirect interference suppression schemes based on resource scheduling, the proposed method can directly perform interference cancellation. This method is not only applicable to multiple demand scenarios within a cellular-free telepathic integrated architecture, but can also be combined with existing indirect interference suppression schemes to further improve system performance, thus having significant implications for the practical deployment of 6G telepathic integrated systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is an overall flow chart of the interference elimination method of the synaesthesia integrated system based on segmented channel estimation;

[0065] Figure 2 This is a comparison chart of the accuracy of the second-stage target detection algorithm;

[0066] Figure 3 This is a comparison chart of communication performance when using different interference cancellation schemes. DETAILED DESCRIPTION

[0067] The present invention will be further explained below with reference to the accompanying drawings.

[0068] In order to better understand the purpose, structure and function of the present invention, the following further describes in detail the interference elimination method of the synaesthesia integration system based on segmented channel estimation of the present invention in conjunction with the accompanying drawings.

[0069] Assume a non-cellular distributed massive MIMO interawareness integration scenario, where there are M = 10 half-duplex APs, of which the number of uplink access node APs is M ul =5, the number of downlink access nodes AP is M dl =5, each access node AP is equipped with N = 4 antennas, and there are K = 8 users in the scenario, of which the number of users with uplink requirements is K ul =4, the number of users with downlink demand is K dl=4. All access nodes AP and users are randomly distributed in an area with a radius of R = 100m. The maximum uplink transmission power of each user is ρ UE =100mW, the maximum downlink transmit power of each access node AP is ρ AP =2W. The path loss exponent of the channel between the access node AP and the user is set to α = 3.7. Each coherence time block lasts 200 symbols, where τ p =5,τ s =10, τ dp =20.

[0070] Based on the above-mentioned non-cellular distributed massive MIMO synaesthesia integration scenario, a synaesthesia integration system interference elimination method based on segmented channel estimation in this embodiment includes the following steps:

[0071] Step 1: Establish a channel model and data transmission model for the non-cellular cooperative interawareness integrated system. All users send uplink pilot signals, and the central processing unit (CPU) estimates the data transmission channel between the user and the access node (AP), where the access node (AP) includes an uplink access node (AP) and a downlink access node (AP).

[0072] Step 1 specifically includes:

[0073] Step 101: In a non-cellular cooperative interawareness integrated system, a regional scene model managed by a central processing unit (CPU) is established; wherein M access nodes (APs) and K users are distributed; and M of the M access nodes (APs) are connected to the network. ul work in uplink mode, and the remaining M dl Work in downlink mode; K users include K ul Uplink demand users and K dl Downlink users; each access point (AP) is equipped with N antennas and connected to the central processing unit (CPU) via a fronthaul link. At the same time, there is a target with an uncertain location in the scenario. The non-cellular cooperative interawareness integrated system needs to simultaneously complete uplink communication with users with uplink needs, downlink communication with users with downlink needs, and perceive the target's moving direction and speed.

[0074] Using the fast fading channel model, the channel conditions in each coherent time block remain unchanged, and the channel in the non-cellular cooperative synaesthesia integrated system scenario is modeled: let k be any integer in the set [1, K], m be any integer in the set [1, M], and the channel vector from the kth user to the mth access node AP is recorded as a vector with N rows and 1 column in, represents the large-scale fading coefficient between the k-th user and the m-th access node AP, express The small-scale fast fading vector, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of I N represents the identity matrix with N rows and columns;

[0075] In the same way, let j be the set [1,K ul ], l is any integer in the set [1,K dl ], the channel from the jth uplink user to the lth downlink user is recorded as a complex number Let u be the set [1,M ul ], i is any integer in the set [1,M dl ] is any integer in the range of , the direct channel without target reflection between the uth uplink access node AP and the ith downlink access node AP is recorded as an N-row N-column complex matrix in, represents the large-scale fading coefficient, express The small-scale fast fading matrix, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of ;

[0076] The existence of the target will cause a channel reflected by the target to exist between the uplink access node AP and the downlink access node AP. The target reflection channel between the uth uplink access node AP and the ith downlink access node AP is recorded as an N-row N-column complex matrix Among them, θ RCS and Represent the path loss coefficient and radar cross section coefficient respectively; a ul,u and a dl,i is a vector with N rows and 1 column, representing the steering vector from the uth uplink access node AP and the ith downlink access node AP to the target, with the superscript symbol (·) H Indicates the conjugate transpose operation on the matrix; since the existence of the target is unknown to the central processing unit CPU, the target existence symbol δ is established T To indicate whether the target appears in the scene, δ T =0 means it does not exist, δ T =1 means existence; since the position of the target is unknown, the CPU obtains the prior target reflection channel through prior knowledge and records it as

[0077] Step 102, the first τ in each coherent time block p symbols are used to estimate the data transmission channel between the user and the access node AP, τ pIndicates the number of symbols occupied in the first stage; in this stage, K users randomly select pilot signals to send, and the uplink pilot signal received by the mth access node AP is represented by an N-line τ p Column matrix For channel estimation from the kth user to the mth access node AP, we need to first Multiply by the pilot signal sent by the kth user get

[0078]

[0079] Among them, ρ p represents the user's pilot transmission power, represents the set of sequence numbers of users using the same pilot as the k-th user and does not include k, represents the channel from the k'th user to the mth access node AP, is the additive Gaussian white noise matrix from the kth user to the mth access node AP, which has a mean of 0 and a variance of The complex Gaussian distribution of

[0080] According to the minimum mean square error (MMSE) channel estimation method, the channel estimation for the kth user to the mth access node AP in this coherent time block is obtained.

[0081]

[0082] in, Indicates taking the mean of the values in the brackets. yes The equivalent large-scale fading coefficient of represents the large-scale fading coefficient of the channel between the kth user and the mth access node AP, represents the large-scale fading coefficient of the channel between the k'th user and the mth access node AP, represents the set of serial numbers of users using the same pilot as the k-th user, express The small-scale fast fading vector, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of The channel estimation error is recorded as represents the channel estimation error vector from the kth user to the mth access node AP.

[0083] Step 2: All downlink access nodes (APs) send a target detection signal, all uplink access nodes (APs) jointly receive the signal and transmit it to the central processing unit (CPU). The CPU detects whether the target is in the scene.

[0084] Step 2 specifically includes:

[0085] Step 201, in each coherent time block (τ p +1)~(τ p +τ s ) symbols are used to detect whether the perceived target is in the scene, τ s Table 2: The number of symbols occupied by the second stage; in this stage, all downlink access nodes AP send target detection signals, and all uplink access nodes AP jointly receive the signals and detect the presence of the perceived target;

[0086] Let t be the set [1,τ s ] is any integer in the tth time slot of this phase, the N rows and 1 column target detection signal received by the uth uplink access node AP Expressed as

[0087]

[0088] in, is the N-row, 1-column detection signal sent by the i-th downlink access node AP in the t-th time slot of the second phase, is the additive white noise received by the u-th uplink access node AP in the t-th time slot of the second phase, which obeys symbol means that it has zero mean and a correlation coefficient of The multivariate cyclically symmetric complex Gaussian distribution of is the variance of the channel noise;

[0089] Step 202: ul The signals received by the uplink access nodes AP in the tth time slot are vertically linked to obtain M ul A vector with N rows and 1 column Represents the signal received by the central processing unit CPU in the tth time slot, where and Represents the 1st and Mth ul The uplink access node AP receives the target detection signal in the tth time slot, and the superscript symbol (·) T Indicates the transposition operation of the matrix; direct channels between all access nodes AP After vectorization, vertical connection follows the distribution symbol Represents a matrix with zero mean and variance R AA The multivariate cyclically symmetric complex Gaussian distribution of It is a direct channel between all access nodes AP The variance matrix of the distribution after vectorization, diag{·} represents the diagonal matrix established with the vector in the brackets as the diagonal, represents the large-scale fading coefficient of the direct channel between the ath uplink access node AP and the bth downlink access node AP, Indicates that both rows and columns are N 2 The identity matrix; the target reflection channel between all access nodes AP After vectorization, vertical connection follows the distribution symbol Indicates that the mean is and the variance matrix R ATA The multivariate cyclically symmetric complex Gaussian distribution of It is the target reflection a priori channel between access nodes APs known to all central processing units CPU The vector connected vertically after vectorization, R ATA is the variance matrix of the distribution obeyed by the target reflection channel between all access nodes AP after vectorization;

[0090] The maximum a posteriori ratio test (MAPRT) is used to use this stage τ s The signal received by the CPU in each time slot is used to detect whether the target exists. The maximum a posteriori ratio test target detection formula Λ is expressed as

[0091]

[0092] in

[0093]

[0094] exp(·) represents the exponential function operation, det(·) represents the determinant operation of the matrix, and ||·|| represents the Euclidean norm operation of the vector; It is the aggregate signal of the sensing signals sent by all downlink access nodes AP in the tth time slot. and Represent the 1st and Mth dl The detection signal sent by the downlink access node AP in the tth time slot of the second phase is: represents the Kronecker product, Indicates that both rows and columns are M ul The identity matrix of

[0095] Set the comparison threshold Λ det,Th , when the central processing unit CPU calculates Λ≥Λ det,Th When the CPU thinks that the target exists in the scene, the target has an estimated symbol When the central processing unit CPU calculates Λ<Λ det,Th When the CPU thinks that the target does not exist in the scene, the target has an estimated symbol

[0096] Step 3: All downlink access nodes (APs) send downlink pilot signals. The central processing unit (CPU) uses the pilot signals received from all uplink access nodes (APs) and the target detection result obtained in step 2 to estimate the cross-link interference channel between the access nodes (APs).

[0097] Step 3 specifically includes:

[0098] Step 301, in each coherent time block (τ p +τ s +1)~(τ p +τ s +τ dp ) symbols are used to estimate the cross-link interference channel between access nodes AP τ dp The number of symbols occupied by the third stage; and when δ T =0 When δ T =1

[0099] In this phase, all antennas of all downlink access nodes AP send mutually orthogonal downlink pilots; let n be any integer in the set [1, N], and the pilot sent by the nth antenna of the i-th downlink access node AP is denoted as The downlink pilot signal received by the uth uplink access node AP Expressed as

[0100]

[0101] Among them, ρ dp is the transmit power of the downlink pilot, represents the channel vector from the nth antenna of the i-th downlink access node AP to the u-th access node AP, is the additive Gaussian white noise matrix of the uth uplink access node AP at this stage, which has a mean of 0 and a variance of The complex Gaussian distribution of

[0102] Step 302: Obtain the channel estimation vector from the nth antenna of the i-th downlink access node AP to the u-th access node AP in this coherent time block according to the minimum mean square error (MMSE) channel estimation method. Expressed as

[0103]

[0104] in, Indicates taking the mean of the values in the brackets, Cov(·,·) indicates taking the covariance matrix operation of the vector in the brackets, At the same time, because the CPU cannot know the target exists symbol δ T , the target existence estimation symbol can only be obtained through the second stage Therefore, it is necessary to δ in T Replace with get That is, the channel estimation from the nth antenna of the i-th downlink access node AP to the u-th access node AP obtained by the central processing unit CPU in the third stage.

[0105] Step 4: The system simultaneously performs uplink and downlink communications and senses the target's moving direction and speed. Based on the channel estimation results obtained in steps 1 and 3, the system performs interference cancellation processing on the received communication and sensing signals respectively.

[0106] Step 4 specifically includes:

[0107] Step 401: The non-cellular cooperative synaesthesia integrated system simultaneously performs uplink and downlink communications and perceives the target's moving direction and speed. At this time, each downlink access node AP sends a synaesthesia integrated signal containing a downlink communication signal and a perception signal. The signal sent by the i-th downlink access node is in, represents the communication precoding vector of the i-th downlink access node to the l-th downlink user, Represents the communication signal to the lth downlink user; represents the perceptual precoding vector of the i-th downlink access node, represents the perception signal of the i-th downlink access node;

[0108] The received signal of the lth downlink user is expressed as:

[0109]

[0110] in, represents the communication signal that the lth downlink user expects to obtain, represents the channel estimation from the lth downlink user to the i-th downlink access node AP; Indicates the communication interference of other downlink users, represents the communication precoding vector of the i-th downlink access node to the l'th downlink user, Represents the communication signal for the l'th downlink user; represents the interference caused by the channel estimation error between the user and the access node AP, represents the channel estimation error from the lth downlink user to the i-th downlink access node AP, represents the communication precoding vector of the i-th downlink access node to the k-th downlink user, represents the communication signal for the kth downlink user; Indicates the interference caused by the perceived signal, represents the channel estimation error from the lth downlink user to the i-th downlink access node AP; represents the cross-link interference, ρ ul,j represents the transmit power of the jth uplink user, represents the communication signal of the jth uplink user; represents the noise interference of the lth downlink user;

[0111] According to the desired signal and interference signal received by the lth downlink user, a high-precision downlink communication signal can be demodulated;

[0112] Step 402: The received signal of the uth uplink access node AP is expressed as

[0113]

[0114] in, Indicates the transmission signal of all uplink users, Indicates the communication signal of all downlink access nodes AP, Represents the noise received by the u-th uplink access node AP at this stage; the estimated channel between access nodes AP obtained in the third stage is eliminated Cross-link interference in

[0115]

[0116] in is the cross-link interference estimation channel matrix from the u-th uplink access node AP to the i-th downlink access node AP, and They represent the channel estimation from the 1st antenna of the i-th downlink access node AP to the u-th access node AP and the channel estimation from the Nth antenna of the i-th downlink access node AP to the u-th access node AP respectively; ρ ul,j represents the transmit power of the jth uplink user, represents the communication signal of the jth uplink user; is the cross-link interference channel matrix from the u-th uplink access node AP to the i-th downlink access node AP;

[0117] The signal of the jth uplink user received by the central processing unit CPU is expressed as:

[0118]

[0119] Among them, v uj represents the maximum ratio combining receiver vector of the jth uplink user’s signal received by the uth uplink access node AP, represents the communication signal that the lth downlink user expects to obtain, represents the channel estimate from the jth uplink user to the uth uplink access node AP; represents the communication interference of other downlink users, ρ ul,j' represents the transmit power of the j'th uplink user, represents the channel estimation from the j'th uplink user to the uth uplink access node AP, represents the communication signal of the j'th uplink user; represents the interference caused by the channel estimation error between the user and the access node AP, ρ ul,k represents the transmit power of the kth uplink user, represents the channel estimation error from the kth uplink user to the uth uplink access node AP, represents the communication signal of the kth uplink user; Indicates the interference caused by the perceived signal, is the cross-link interference estimation channel error matrix from the u-th uplink access node AP to the i-th downlink access node AP; Indicates cross-link interference; Indicates noise interference;

[0120] The CPU can demodulate the high-precision uplink communication signal based on the desired signal and interference signal of the jth uplink user received by the CPU.

[0121] Step 403: The signal received by the uth uplink access node AP When performing sensory signal detection, it is reformulated as:

[0122]

[0123] in, represents the perception signal that the u-th uplink access node AP expects to obtain; Indicates uplink communication signal interference, represents the channel vector from the kth uplink user to the uth uplink access node AP; Indicates downlink communication signal interference;

[0124] Based on the decoding of the uplink and downlink communication signals in steps 401 and 402, After communication interference elimination, it is expressed as in, Indicates the residual uplink communication signal interference after interference elimination. is the decoding error of the u-th uplink user signal; Indicates the residual downlink communication signal interference after interference elimination;

[0125] A high-precision perception signal can be demodulated based on the perception expectation signal and the perception interference signal received by the central processing unit CPU.

[0126] Figure 1 This is an overall flow chart of a method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation according to the present invention.

[0127] Figure 2 This is a comparison chart of the accuracy of the second-stage target detection algorithm, showing the accuracy of the MAPRT target detector in the stage symbol number τ s and the detector threshold Λ det,Th The false alarm probability P when taking different values fa , missed detection probability P md And the correct detection probability P d It reveals that increasing τ s More detection support data can be provided, which improves the accuracy of detection, but the gains gradually decrease. s =10 to 20 is significantly less accurate than the gain from 5 to 10. det,Th The value of p also seriously affects fa and p md For our simulations, we set Λ det,Th =250, which results in a detection probability of 0.925.

[0128] Figure 3 It is a comparison chart of communication performance when different interference elimination schemes are adopted, comparing the performance when the target exists (δ T =1) and does not exist (δ T =0), the improvement of spectrum efficiency after adopting different interference elimination strategies. w / o(δ T =1) and w / o(δ T =0) respectively represent the uplink and rate when there is / is not a target in the scene without using the interference cancellation scheme; w / e with δ T (δ T =1) with w / e withδ T (δ T=0) respectively represent the uplink and rate when the ideal interference cancellation scheme is used when there is / is not a target in the scene, i.e., target detection error is not considered; w / e with w / o(δ T =1) and w / o(δ T = 0) clearly shows the performance degradation caused by the target reflection channel. Taking into account the impact of target detection error, the uplink sum rate can still reach 95% of w / c. This proves that the proposed interference management mechanism can effectively and directly suppress interference.

[0129] In summary, the present invention addresses the interference suppression problem in the scenario of cooperative interawareness integration of non-cellular massive MIMO systems and proposes a method for interference elimination of an interawareness integration system based on segmented channel estimation. The present invention first establishes a model of channels, transmission signals, and interference according to the system scenario. Then, the estimated channel and estimated error channel of data transmission between the user and the access node AP after sending the uplink pilot are derived. Then, a target detection inequality is established to detect whether there is a perception target in the scenario, and the estimated channel and estimated error channel of cross-link interference between APs after sending the downlink pilot are derived. Finally, an interference elimination method and a sequential processing order based on the estimated channel are proposed when full-duplex communication and target perception are carried out simultaneously. Compared with the existing indirect interference suppression scheme based on resource scheduling, the method proposed in the present invention can directly eliminate interference. It is not only applicable to multiple demand scenarios under the non-cellular interawareness integration architecture, but also can be combined with the existing indirect interference suppression scheme to further improve system performance, which is of great significance to the actual deployment of 6G interawareness integration.

[0130] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation, characterized by: The following steps are involved: Step 1: Establish a channel model and data transmission model for the non-cellular cooperative interawareness integrated system. All users send uplink pilot signals, and the central processing unit (CPU) estimates the data transmission channel between the user and the access node (AP), where the access node (AP) includes an uplink access node (AP) and a downlink access node (AP). Step 2: All downlink access nodes (APs) send a target detection signal, all uplink access nodes (APs) jointly receive the signal and transmit it to the central processing unit (CPU). The CPU detects whether the target is in the scene. Step 3: All downlink access nodes (APs) send downlink pilot signals. The central processing unit (CPU) uses the pilot signals received from all uplink access nodes (APs) and the target detection result obtained in step 2 to estimate the cross-link interference channel between the access nodes (APs). The step 3 specifically includes: Step 301, in each coherent time block (τ p +τ s +1)~(τ p +τ s +τ dp ) symbols are used to estimate the cross-link interference channel between access nodes AP τ p represents the number of symbols occupied in the first stage, τ s The number of symbols occupied by the second stage, τ dp The number of symbols occupied by the third stage; and when δ T =0 When δ T =1 Among them, δ T is the target presence symbol, indicating whether the target appears in the scene, δ T =0 means it does not exist, δ T =1 means existence; Indicates the direct channel between all access nodes AP, Indicates the target reflection channel between all access nodes AP; In this phase, all antennas of all downlink access nodes AP send mutually orthogonal downlink pilots; Step 302: Obtain the channel estimation vector from the nth antenna of the i-th downlink access node AP to the u-th access node AP in this coherent time block according to the minimum mean square error (MMSE) channel estimation method. Expressed as in, Indicates taking the mean of the values in the brackets, Cov(·,·) indicates taking the covariance matrix operation of the vector in the brackets, At the same time, because the CPU cannot know the target exists symbol δ T , the target existence estimation symbol can only be obtained through the second stage Therefore, it is necessary to δ in T Replace with get That is, the channel estimate from the nth antenna of the i-th downlink access node AP to the u-th access node AP obtained by the central processing unit CPU in the third stage; In step 4, the non-cellular cooperative interawareness integrated system simultaneously performs uplink and downlink communications and perceives the target's moving direction and speed, and performs interference elimination processing on the received communication and perception signals based on the channel estimation results obtained in steps 1 and 3.

2. The method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation according to claim 1, characterized in that: The step 1 specifically includes: Step 101: In a non-cellular cooperative interawareness integrated system, a regional scene model managed by a central processing unit (CPU) is established; wherein M access nodes (APs) and K users are distributed; and M of the M access nodes (APs) are connected to the network. ul work in uplink mode, and the remaining M dl Work in downlink mode; K users include K ul Uplink demand users and K dl Downlink users; each access point (AP) is equipped with N antennas and connected to the central processing unit (CPU) via a fronthaul link. At the same time, there is a target with an uncertain location in the scenario. The non-cellular cooperative interawareness integrated system needs to simultaneously complete uplink communication with users with uplink needs, downlink communication with users with downlink needs, and perceive the target's moving direction and speed. Using the fast fading channel model, the channel conditions in each coherent time block remain unchanged, and the channel in the non-cellular cooperative synaesthesia integrated system scenario is modeled: let k be any integer in the set [1, K], m be any integer in the set [1, M], and the channel vector from the kth user to the mth access node AP is recorded as a vector with N rows and 1 column in, represents the large-scale fading coefficient between the k-th user and the m-th access node AP, express The small-scale fast fading vector, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of I N represents the identity matrix with N rows and columns; In the same way, let j be the set [1,K ul ], l is any integer in the set [1,K dl ], the channel from the jth uplink user to the lth downlink user is recorded as a complex number Let u be the set [1,M ul ], i is any integer in the set [1,M dl ] is any integer in the range of , the direct channel without target reflection between the uth uplink access node AP and the ith downlink access node AP is recorded as an N-row N-column complex matrix in, represents the large-scale fading coefficient, express The small-scale fast fading matrix, which has a mean of 0 and a correlation matrix of I N Multivariate cyclically symmetric complex Gaussian distribution of ; The existence of the target will cause a channel reflected by the target to exist between the uplink access node AP and the downlink access node AP. The target reflection channel between the uth uplink access node AP and the ith downlink access node AP is recorded as an N-row N-column complex matrix Among them, θ RCS and Represent the path loss coefficient and radar cross section coefficient respectively; a ul,u and a dl,i is a vector with N rows and 1 column, representing the steering vector from the uth uplink access node AP and the ith downlink access node AP to the target, with the superscript symbol (·) H Indicates the conjugate transpose operation on the matrix; since the existence of the target is unknown to the central processing unit CPU, the target existence symbol δ is established T To indicate whether the target appears in the scene, δ T =0 means it does not exist, δ T =1 means existence; since the position of the target is unknown, the CPU obtains the prior target reflection channel through prior knowledge and records it as Step 102, the first τ in each coherent time block p symbols are used to estimate the data transmission channel between the user and the access node AP, τ p Indicates the number of symbols occupied in the first stage; in this stage, K users randomly select pilot signals to send, and the uplink pilot signal received by the mth access node AP is represented by an N-line τ p Column matrix For channel estimation from the kth user to the mth access node AP, we need to first Multiply by the pilot signal sent by the kth user get Among them, ρ p represents the user's pilot transmission power, represents the set of sequence numbers of users using the same pilot as the k-th user and does not include k, represents the channel from the k′th user to the mth access node AP, is the additive Gaussian white noise matrix from the kth user to the mth access node AP, which has a mean of 0 and a variance of The complex Gaussian distribution of According to the minimum mean square error (MMSE) channel estimation method, the channel estimation for the kth user to the mth access node AP in this coherent time block is obtained. in, Indicates taking the mean of the values in the brackets. yes The equivalent large-scale fading coefficient of represents the large-scale fading coefficient of the channel between the kth user and the mth access node AP, represents the large-scale fading coefficient of the channel between the k′th user and the mth access node AP, represents the set of serial numbers of users using the same pilot as the k-th user, express The small-scale fast fading vector, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of The channel estimation error is recorded as represents the channel estimation error vector from the kth user to the mth access node AP.

3. The method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation according to claim 1, characterized in that: The step 2 specifically includes: Step 201, in each coherent time block (τ p +1)~(τ p +τ s ) symbols are used to detect whether the perceived target is in the scene, τ s Table 2: The number of symbols occupied by the second stage; in this stage, all downlink access nodes AP send target detection signals, and all uplink access nodes AP jointly receive the signals and detect the presence of the perceived target; Let t be the set [1,τ s ] is any integer in the tth time slot of this phase, the N rows and 1 column target detection signal received by the uth uplink access node AP Expressed as in, is the N-row, 1-column detection signal sent by the i-th downlink access node AP in the t-th time slot of the second phase, is the additive white noise received by the u-th uplink access node AP in the t-th time slot of the second phase, which obeys symbol It has zero mean and correlation coefficient is The multivariate cyclically symmetric complex Gaussian distribution of is the variance of the channel noise; Step 202: ul The signals received by the uplink access nodes AP in the tth time slot are vertically linked to obtain M ul A vector with N rows and 1 column Represents the signal received by the central processing unit CPU in the tth time slot, where and Represent the 1st and Mth ul The uplink access node AP receives the target detection signal in the tth time slot, and the superscript symbol (·) T Indicates the transposition operation of the matrix; direct channels between all access nodes AP After vectorization, vertical connection follows the distribution symbol Represents a matrix with zero mean and variance R AA The multivariate cyclically symmetric complex Gaussian distribution of It is a direct channel between all access nodes AP The variance matrix of the distribution after vectorization, diag{·} represents the diagonal matrix established with the vector in the brackets as the diagonal, represents the large-scale fading coefficient of the direct channel between the ath uplink access node AP and the bth downlink access node AP, Indicates that both rows and columns are N 2 The identity matrix; the target reflection channel between all access nodes AP After vectorization, vertical connection follows the distribution symbol Indicates that the mean is and the variance matrix R ATA The multivariate cyclically symmetric complex Gaussian distribution of It is the target reflection a priori channel between access nodes APs known to all central processing units CPU The vector connected vertically after vectorization, R ATA is the variance matrix of the distribution obeyed by the target reflection channel between all access nodes AP after vectorization; The maximum a posteriori ratio test (MAPRT) is used to use this stage τ s The signal received by the CPU in each time slot is used to detect whether the target exists. The maximum a posteriori ratio test target detection formula Λ is expressed as in exp(·) represents the exponential function operation, det(·) represents the determinant operation of the matrix, and ||·|| represents the Euclidean norm operation of the vector; It is the aggregate signal of the sensing signals sent by all downlink access nodes AP in the tth time slot. and Represent the 1st and Mth dl The detection signal sent by the downlink access node AP in the tth time slot of the second phase is: represents the Kronecker product, Indicates that both rows and columns are M ul The identity matrix of Set the comparison threshold Λ det,Th , when the central processing unit CPU calculates Λ≥Λ det,Th When the CPU thinks that the target exists in the scene, the target has an estimated symbol When the central processing unit CPU calculates Λ<Λ det,Th When the CPU thinks that the target does not exist in the scene, the target has an estimated symbol 4. The method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation according to claim 1, characterized in that: In step 301, let n be any integer in the set [1, N], and the pilot signal sent by the nth antenna of the i-th downlink access node AP is recorded as The downlink pilot signal received by the uth uplink access node AP Expressed as Among them, ρ dp is the transmit power of the downlink pilot, represents the channel vector from the nth antenna of the i-th downlink access node AP to the u-th access node AP, is the additive Gaussian white noise matrix of the uth uplink access node AP at this stage, which has a mean of 0 and a variance of The complex Gaussian distribution of .

5. The method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation according to claim 1, characterized in that: The step 4 specifically includes: Step 401: The non-cellular cooperative synaesthesia integrated system simultaneously performs uplink and downlink communications and perceives the target's moving direction and speed. At this time, each downlink access node AP sends a synaesthesia integrated signal containing a downlink communication signal and a perception signal. The signal sent by the i-th downlink access node is in, represents the communication precoding vector of the i-th downlink access node to the l-th downlink user, Represents the communication signal to the lth downlink user; represents the perceptual precoding vector of the i-th downlink access node, represents the perception signal of the i-th downlink access node; The received signal of the lth downlink user is expressed as: in, represents the communication signal that the lth downlink user expects to obtain, represents the channel estimation from the lth downlink user to the i-th downlink access node AP; Indicates the communication interference of other downlink users, represents the communication precoding vector of the i-th downlink access node to the l′th downlink user, represents the communication signal for the l′th downlink user; represents the interference caused by the channel estimation error between the user and the access node AP, represents the channel estimation error from the lth downlink user to the i-th downlink access node AP, represents the communication precoding vector of the i-th downlink access node to the k-th downlink user, represents the communication signal for the kth downlink user; Indicates the interference caused by the perceived signal, represents the channel estimation error from the lth downlink user to the i-th downlink access node AP; represents the cross-link interference, ρ ul,j represents the transmit power of the jth uplink user, represents the communication signal of the jth uplink user; represents the noise interference of the lth downlink user; According to the desired signal and interference signal received by the lth downlink user, a high-precision downlink communication signal can be demodulated; Step 402: The received signal of the uth uplink access node AP is expressed as in, Indicates the transmission signal of all uplink users, Indicates the communication signal of all downlink access nodes AP, Represents the noise received by the u-th uplink access node AP at this stage; the estimated channel between access nodes AP obtained in the third stage is eliminated Cross-link interference in in is the cross-link interference estimation channel matrix from the u-th uplink access node AP to the i-th downlink access node AP, and They represent the channel estimation from the 1st antenna of the i-th downlink access node AP to the u-th access node AP and the channel estimation from the Nth antenna of the i-th downlink access node AP to the u-th access node AP respectively; ρ ul,j represents the transmit power of the jth uplink user, represents the communication signal of the jth uplink user; is the cross-link interference channel matrix from the u-th uplink access node AP to the i-th downlink access node AP; The signal of the jth uplink user received by the central processing unit CPU is expressed as: Among them, v uj represents the maximum ratio combining receiver vector of the jth uplink user’s signal received by the uth uplink access node AP, represents the communication signal that the lth downlink user expects to obtain, represents the channel estimate from the jth uplink user to the uth uplink access node AP; represents the communication interference of other downlink users, ρ ul,j′ represents the transmit power of the j′th uplink user, represents the channel estimation from the j′th uplink user to the uth uplink access node AP, represents the communication signal of the j′th uplink user; represents the interference caused by the channel estimation error between the user and the access node AP, ρ ul,k represents the transmit power of the kth uplink user, represents the channel estimation error from the kth uplink user to the uth uplink access node AP, represents the communication signal of the kth uplink user; Indicates the interference caused by the perceived signal, is the cross-link interference estimation channel error matrix from the u-th uplink access node AP to the i-th downlink access node AP; Indicates cross-link interference; Indicates noise interference; The CPU can demodulate the high-precision uplink communication signal based on the desired signal and interference signal of the jth uplink user received by the CPU. Step 403: The signal received by the uth uplink access node AP When performing sensory signal detection, it is reformulated as: in, represents the perception signal that the u-th uplink access node AP expects to obtain; Indicates uplink communication signal interference, represents the channel vector from the kth uplink user to the uth uplink access node AP; Indicates downlink communication signal interference; Based on the decoding of the uplink and downlink communication signals in steps 401 and 402, After communication interference elimination, it is expressed as in, Indicates the residual uplink communication signal interference after interference elimination. is the decoding error of the u-th uplink user signal; Indicates the residual downlink communication signal interference after interference elimination; A high-precision perception signal can be demodulated based on the perception expectation signal and the perception interference signal received by the central processing unit CPU.

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